![]() ![]() darktable is meant to process raw photographs, mostly coming from dedicated cameras (high-end point-and-shoot, DSLR, mirrorless) costing at least 800 €, which is too expensive for younger folk (or may be a low-priority expense given what smartphones can achieve now).younger folks use their smartphone and mobile apps to take and edit photos,.The population of darktable users is therefore a non-randomly filtered subset of the general population of computer users, which clearly indicates darktable fails to reach or to appeal to younger folks. This should be compared with the age distribution of other imaging software to conclude, many factors could explain it : By comparison, the folks below 35 and above 65 are under-represented in the survey, but everybody above 35 is over-represented on my channel. It is immediately clear that the US population of internet users has a flat distribution and that both the survey and Youtube show a an abnormal peak between 40 and 50. The statistics used here cover the years 2019, 2020, 2021 in full, which include 309 210 views. This is to be taken with precaution though, because my videos are sometimes posted in French, sometimes in English, and they tend to dive deeper into the technicalities than the average. In any case, it might be interesting to see how they compare. I also used here the age distribution of the viewers of my Youtube channel, dedicated to photo editing with darktable since 2016. The ratio of internet users is between 99 and 96 % for all age classes, except for the 65+ where it drops to 75 %. Using the USA population as a control sample, I took the age distribution in the general population in early 2020 from the United States Census Bureau, cut it into age classes, and estimated the number of internet users from the 2021 ratios given by the Pew Research Center. Then, I want to assess if the population of darktable users is a random subset of the population of digital photographers, or if it is non-randomly biased by some effect. But since there are no such figures for photographers, the next best metric is the general population of internet users. To do so, we need to check if the age distribution matches the age distribution of computer users. The countries were recorded based on the IP addresses and may be wrong if a VPN was used. The results from 59 countries were recorded, but only 35 countries had at least 3 respondents. The survey cost me a monthly subscription to , that is around 40 $ out of my own pocket. This article is rendered from Markdown and Plotly HTML exports on WordPress using my own plugin : WP Scholar. The color scales used in the graphs have been designed for perceptual uniformity using the darktable UCS 2022 color space Python code and Colour. ![]() The Python code written for this task has been turned into a library of functions that can be reused in the future. ![]() The raw data has been exported from in CSV and post-processed in Python with Pandas, Numpy and the graphs are rendered using Plotly. The polling system () recorded IP addresses and user-agent to prevent people from taking the survey more than once. 1085 respondents answered all questions. Between 20, 66 persons have contributed to darktable source code, so we can expect that at most 6 % of the respondents are developers and contributors of the project. It is to be noted that it was not relayed on Github or any other code hosting platform, though the IRC channel is populated with developers and power-users, so the respondents are expected to be mostly users and not contributors.ġ101 respondents from 59 countries participated between March 6th 2020 and March 20th 2020. possibly on other chats and platforms I am not aware of.The survey was conducted in English, on the internet, using to record answers. It had a total of 26 questions. The link to the survey was posted : In 2020, I ran a survey of the darktable user base to gather actual data. Since these past 2 years have been hectic, dev-wise, I only got to process the data this summer. This is unfortunately overlooked in FLOSS and it is often not well regarded to collect user data. But then, developers will justify their design by referring to the “average user” as a fantasized entity, undefined and certainly not understood. ![]() The core basics of design are to know for whom you design, that is who are the users of your solution, what they expect and what they need. It is also necessary to assess if the actual user of your product is the one you designed it for in the first place, that is, who is missing from your user base, to avoid the survivor bias. ![]()
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